Overview

Dataset statistics

Number of variables5
Number of observations918
Missing cells108
Missing cells (%)2.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.8 KiB
Average record size in memory42.1 B

Variable types

Numeric2
Text1
DateTime2

Dataset

Description한국토지주택공사에서 시행한 보상공고 현황(사업지구코드, 사업지구명, 보상시작일자, 보상종료일자 등)의 자료를 제공합니다.
Author한국토지주택공사
URLhttps://www.data.go.kr/data/15122809/fileData.do

Alerts

보상시작일자 has 35 (3.8%) missing valuesMissing
보상종료일자 has 73 (8.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:49:33.809998
Analysis finished2023-12-12 05:49:35.135343
Duration1.33 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업지구코드
Real number (ℝ)

Distinct461
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156234.66
Minimum100187
Maximum901660
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2023-12-12T14:49:35.252258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100187
5-th percentile100261.85
Q1100339.5
median101403
Q3104877.5
95-th percentile300192.45
Maximum901660
Range801473
Interquartile range (IQR)4538

Descriptive statistics

Standard deviation174136.75
Coefficient of variation (CV)1.1145846
Kurtosis12.77313
Mean156234.66
Median Absolute Deviation (MAD)1114
Skewness3.6882318
Sum1.4342342 × 108
Variance3.0323609 × 1010
MonotonicityIncreasing
2023-12-12T14:49:35.454086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100289 39
 
4.2%
100266 30
 
3.3%
100322 29
 
3.2%
100276 17
 
1.9%
101578 10
 
1.1%
101706 10
 
1.1%
100428 9
 
1.0%
101458 9
 
1.0%
100770 8
 
0.9%
100576 8
 
0.9%
Other values (451) 749
81.6%
ValueCountFrequency (%)
100187 1
 
0.1%
100198 1
 
0.1%
100221 1
 
0.1%
100223 4
0.4%
100224 1
 
0.1%
100232 2
0.2%
100233 1
 
0.1%
100235 3
0.3%
100236 1
 
0.1%
100237 2
0.2%
ValueCountFrequency (%)
901660 1
0.1%
901557 1
0.1%
901164 1
0.1%
901114 1
0.1%
900922 1
0.1%
900907 1
0.1%
900906 1
0.1%
900717 1
0.1%
900447 1
0.1%
900169 1
0.1%

사업지구명
Text

Distinct461
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2023-12-12T14:49:35.809670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length6.8823529
Min length2

Characters and Unicode

Total characters6318
Distinct characters304
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)32.2%

Sample

1st row수원영통
2nd row순천연향2
3rd row횡성읍마
4th row광주신창
5th row광주신창
ValueCountFrequency (%)
용인죽전 39
 
4.2%
용인동백 30
 
3.2%
화성동탄 29
 
3.1%
원주무실2 17
 
1.8%
수원고등(05주환3 10
 
1.1%
하남미사(09보금3 10
 
1.1%
광명소하(02gb 9
 
1.0%
남양뉴타운 9
 
1.0%
군부대매봉산 8
 
0.9%
화성동탄2 8
 
0.9%
Other values (464) 765
81.9%
2023-12-12T14:49:36.380505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 333
 
5.3%
( 333
 
5.3%
주 231
 
3.7%
0 184
 
2.9%
산 162
 
2.6%
2 136
 
2.2%
동 126
 
2.0%
천 123
 
1.9%
인 116
 
1.8%
성 109
 
1.7%
Other values (294) 4465
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4740
75.0%
Decimal Number 613
 
9.7%
Close Punctuation 333
 
5.3%
Open Punctuation 333
 
5.3%
Uppercase Letter 235
 
3.7%
Dash Punctuation 39
 
0.6%
Space Separator 16
 
0.3%
Lowercase Letter 4
 
0.1%
Other Punctuation 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 231
 
4.9%
산 162
 
3.4%
동 126
 
2.7%
천 123
 
2.6%
인 116
 
2.4%
성 109
 
2.3%
양 105
 
2.2%
대 101
 
2.1%
용 99
 
2.1%
전 97
 
2.0%
Other values (265) 3471
73.2%
Uppercase Letter
ValueCountFrequency (%)
B 108
46.0%
L 79
33.6%
G 29
 
12.3%
R 5
 
2.1%
D 5
 
2.1%
T 2
 
0.9%
K 2
 
0.9%
X 2
 
0.9%
A 1
 
0.4%
M 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
0 184
30.0%
2 136
22.2%
1 66
 
10.8%
5 54
 
8.8%
3 50
 
8.2%
6 33
 
5.4%
9 30
 
4.9%
8 26
 
4.2%
7 23
 
3.8%
4 11
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
& 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 333
100.0%
Open Punctuation
ValueCountFrequency (%)
( 333
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4740
75.0%
Common 1339
 
21.2%
Latin 239
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 231
 
4.9%
산 162
 
3.4%
동 126
 
2.7%
천 123
 
2.6%
인 116
 
2.4%
성 109
 
2.3%
양 105
 
2.2%
대 101
 
2.1%
용 99
 
2.1%
전 97
 
2.0%
Other values (265) 3471
73.2%
Common
ValueCountFrequency (%)
) 333
24.9%
( 333
24.9%
0 184
13.7%
2 136
10.2%
1 66
 
4.9%
5 54
 
4.0%
3 50
 
3.7%
- 39
 
2.9%
6 33
 
2.5%
9 30
 
2.2%
Other values (7) 81
 
6.0%
Latin
ValueCountFrequency (%)
B 108
45.2%
L 79
33.1%
G 29
 
12.1%
R 5
 
2.1%
D 5
 
2.1%
n 4
 
1.7%
T 2
 
0.8%
K 2
 
0.8%
X 2
 
0.8%
A 1
 
0.4%
Other values (2) 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4740
75.0%
ASCII 1578
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 333
21.1%
( 333
21.1%
0 184
11.7%
2 136
8.6%
B 108
 
6.8%
L 79
 
5.0%
1 66
 
4.2%
5 54
 
3.4%
3 50
 
3.2%
- 39
 
2.5%
Other values (19) 196
12.4%
Hangul
ValueCountFrequency (%)
주 231
 
4.9%
산 162
 
3.4%
동 126
 
2.7%
천 123
 
2.6%
인 116
 
2.4%
성 109
 
2.3%
양 105
 
2.2%
대 101
 
2.1%
용 99
 
2.1%
전 97
 
2.0%
Other values (265) 3471
73.2%

보상공고일련번호
Real number (ℝ)

Distinct46
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0501089
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2023-12-12T14:49:36.597656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile20
Maximum46
Range45
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.8811134
Coefficient of variation (CV)1.6989947
Kurtosis12.858883
Mean4.0501089
Median Absolute Deviation (MAD)1
Skewness3.4687766
Sum3718
Variance47.349722
MonotonicityNot monotonic
2023-12-12T14:49:36.774324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 455
49.6%
2 162
 
17.6%
3 84
 
9.2%
4 45
 
4.9%
5 31
 
3.4%
6 20
 
2.2%
7 14
 
1.5%
8 11
 
1.2%
9 8
 
0.9%
10 6
 
0.7%
Other values (36) 82
 
8.9%
ValueCountFrequency (%)
1 455
49.6%
2 162
 
17.6%
3 84
 
9.2%
4 45
 
4.9%
5 31
 
3.4%
6 20
 
2.2%
7 14
 
1.5%
8 11
 
1.2%
9 8
 
0.9%
10 6
 
0.7%
ValueCountFrequency (%)
46 1
0.1%
45 1
0.1%
44 1
0.1%
43 1
0.1%
42 1
0.1%
41 1
0.1%
40 1
0.1%
39 1
0.1%
38 1
0.1%
37 1
0.1%

보상시작일자
Date

MISSING 

Distinct695
Distinct (%)78.7%
Missing35
Missing (%)3.8%
Memory size7.3 KiB
Minimum1997-02-17 00:00:00
Maximum2023-08-07 00:00:00
2023-12-12T14:49:36.986681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:37.207280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보상종료일자
Date

MISSING 

Distinct656
Distinct (%)77.6%
Missing73
Missing (%)8.0%
Memory size7.3 KiB
Minimum1997-12-23 00:00:00
Maximum2023-08-21 00:00:00
2023-12-12T14:49:37.373270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:37.564175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T14:49:34.426821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:34.093016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:34.608679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:49:34.269758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:49:37.694883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업지구코드보상공고일련번호
사업지구코드1.0000.091
보상공고일련번호0.0911.000
2023-12-12T14:49:37.780557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업지구코드보상공고일련번호
사업지구코드1.000-0.452
보상공고일련번호-0.4521.000

Missing values

2023-12-12T14:49:34.777345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:49:34.930526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T14:49:35.068481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

사업지구코드사업지구명보상공고일련번호보상시작일자보상종료일자
0100187수원영통12000-06-212000-08-20
1100198순천연향211997-02-171997-12-23
2100221횡성읍마11999-03-031999-03-16
3100223광주신창12001-09-172001-11-16
4100223광주신창22002-12-022003-02-01
5100223광주신창32003-04-042003-05-03
6100223광주신창42004-05-312004-06-12
7100224대구칠곡311999-12-202000-02-20
8100232대전노은111999-01-141999-02-13
9100232대전노은121999-06-071999-07-31
사업지구코드사업지구명보상공고일련번호보상시작일자보상종료일자
908900169낙동강지구212009-09-262009-09-26
909900447현내-송현간도로공사(02수탁)12012-05-152012-06-29
910900717창원동읍우회도로12011-07-042011-08-05
911900906영월북쌍12016-08-222016-09-05
912900907남원주역세권12017-09-042017-09-18
913900922전남담양12015-05-262015-05-26
914901114밀양나노융합센터12016-03-182016-04-04
915901164괴산미니복합타운12020-03-252020-04-08
916901557광명너부대(수탁보상)12020-10-152020-10-30
917901660무주(반디나래지원센터)12021-07-272021-08-11